code: def __init__(self, args: dict):
      BaseDiscriminator.__init__(self)
  
      self.discriminator_input_dim = args.discriminator_input_dim
  
      layers = nn.ModuleList()
  
      layers.append(
          nn.Sequential(
              nn.Linear(np.prod(args.discriminator_input_dim), 256),
              nn.ReLU(),
          )
      )
  
      layers.append(nn.Sequential(nn.Linear(256, 1), nn.Sigmoid()))
  
      self.layers = layers
      self.depth = len(layers)
  
imports: from typing import List
  import numpy
  import torch
  import torch.nn
  from pythae.models.nn import BaseDecoder, BaseDiscriminator, BaseEncoder, BaseMetric
  from ..base.base_utils import ModelOutput
label_desc: Use image node_id 1 to create a new Discriminator_MLP object from inherited base classes: BaseDiscriminator with example: obj = Discriminator_MLP(args)